RF fingerprinting is a method for locating the position of a mobile unit (MU) in a wireless communication network. RF fingerprinting is described generally in U.S. Pat. No. 6,269,246.
RF fingerprinting is particularly useful in indoor settings where technologies such as GPS are typically not reliable. It works with information already available in indoor settings, such as the received signal strength indicator (RSSI or signal strength) obtainable from an IEEE 802.11 network installed to provide wireless connectivity, and does not require any additional hardware. As such, RF fingerprinting is a good technique for determining MU location in a wireless environment without requiring the installation of additional hardware.
There are several known variations in RF fingerprinting technology. Prominent examples include: 1) selection of what portion of the RF spectrum to scan; 2) different techniques for generating the RF fingerprint database; and 3) different search algorithms for determining the closest matching fingerprint.
The resolution of location determination is largely controlled by how far apart the fingerprint samples are taken. The closer they are, the higher the resolution. Of course, a person skilled in the art can appreciate that the resolution is limited by the sensitivity of the fingerprint measuring device. In addition, if two fingerprints for different locations look too much alike (e.g., due to insufficient sensitivity in the measuring device), then accuracy is lessened.
Thus, there exists a need for a method for extending RF fingerprinting to provide real-time, high resolution location estimates of a MU in a wireless communication environment. For purposes of this disclosure, “real-time” means the production of location estimates close to once per second. “High resolution” means resolution on the order of distinguishing between office cubicles (i.e., 2-3 meters) rather than between buildings. There also exists a need for a method to cope with ambiguous RF environments in which two locations that should be distinguishable are not.
Techniques included in that method should include the following: 1) techniques for preprocessing raw RF samples to derive an RF fingerprint; 2) techniques for searching for RF fingerprint matches; and 3) techniques for filtering multiple RF fingerprint matches and presenting a single best estimate.
As stated before, there exists a need to improve RF fingerprinting in ambiguous RF environments. An RF environment is ambiguous for the purposes of location determination when two distinct locations cannot be distinguished, based on their RF fingerprints, with a desired probability of success. This can happen because the sensitivity of the measuring device is insufficient to distinguish between the RF fingerprints at the locations. It can also happen because the RSSI data at one or more of the locations is relatively unstable. This means that the signal strength changes in unpredictable ways (e.g., a signal strength that is often +/−4 dBm different than recorded in the RF fingerprint).
The prior art does not address unpredictable variation, as opposed to predictable variation, such as a transmitter that powers down at the same time every day. Unpredictable variation can have many causes, such as: 1) multipath effects; 2) transitory obstacles between the MU and a transmitter (e.g., a person walking by); and 3) temporary environmental changes (e.g., a door opening and closing).
Another cause for an RF environment to be ambiguous relates to the placement of transmitters which can result in aliasing problems. Two distinct locations can have the same RF fingerprint given a particular transmitter placement. See FIG. 1 for an example. FIG. 1 is an illustration of an aliasing problem. A MU at each location on the ring around transmitter 1 receives the same strength signal from transmitter 1; each location on the ring is an alias (i.e., has the same RF signature) of all other locations on the ring. Likewise for a MU at each location around transmitter 2 with respect to transmitter 2. While adding a second transmitter usually clears up such ambiguities, not all are necessarily removed. At the two locations 3 and 4, the RF environment is indistinguishable, even with two transmitters.
There also exists a need to improve RF fingerprinting for real-time MU location determination. Real-time location determination attempts to keep track of a MU as it moves about in an environment. This has many useful applications, such as being able to offer location specific directions as a MU user moves around in an unfamiliar environment. To offer real-time location determination, location estimates must be produced relatively often (e.g., close to once per second as opposed to a couple of times per minute).
This introduces two new problems to basic RF fingerprinting techniques. First, when gathering data to generate an RF fingerprint, signals may not be observable from all transmitters used in generating the fingerprint. This can have several meanings, none of which are distinguishable at the MU. For instance, 1) the signal from the transmitter is too weak to be observed by the MU at its current location; 2) the transmitter may not be transmitting as often as the MU is observing (e.g., if a MU produces an RF signature once per second and a transmitter used in producing RF fingerprints only transmits once per second, then some RF fingerprints will not include new data for that transmitter); and 3) the transmitter may be transmitting often enough, but the signal may collide with another transmission and not be observed. Therefore, when each RF fingerprint is generated, some interpretation must be assigned to transmitters from which no signal was observed since the last RF fingerprint was generated.
For example, consider the following sequence of signal strength measurements for a particular transmitter: 47, 45, 41, 0, 43, 44, 0, 47 and 46. There are two time slices at which no signal can be observed for the transmitter (denoted by zeros for the signal strength measurement). Looking at the data before and after these time slices (and assuming that signals are being sampled relatively quickly), the inventors of the present invention, unlike the prior art, can deduce that the transmitter signal is not likely to be too weak to be observed in these time slices. In contrast to the prior art, the present invention takes into account that it is more likely that some intermittent problem has temporarily prevented the transmitter's signal from being observed.
On the other hand, consider the following sequence: 20, 18, 0, 16, 14, 0, 0, 5, 0, 0, 0 and 0. While the inventors of the present invention could similarly deduce that the first time slice in which the signal could not be observed is likely to be due to an intermittent problem, the subsequent time slices in which the signal could not be observed are more likely to be due to the transmitter's signal being too weak. The present inventors base this conclusion on the consistent weakening of the signal, which is likely to represent movement away from the transmitter, and the longer sequence of consecutive time slices in which the transmitter's signal could not be observed. Such techniques are not described in the prior art.
The second problem related to producing frequent location estimates is that producing a new location estimate each time a new RF fingerprint is generated can result in a jittery series of estimates. When a rapid series of changing location estimates is presented to a user, the user's confidence in the estimates drops significantly. Two examples of such jitter problems are shown in FIG. 2 and FIG. 3. In FIG. 2, a user is standing between locations 10 and 20. In such a situation, a bad series of estimates would jitter between 10 and 20, with no stability at either location. In FIG. 3, the user is standing near locations 10a and 30a. This is similar to FIG. 2 in which jitter between 10 and 20 would be unreliable, but user confidence would be even lower because it is physically impossible to move back and forth through the wall 40a having a door 50a separating the locations. Thus, there exists a great need to resolve said jittery estimates.